Nowadays several medical image acquisition techniques exist that render a digital signal representation of a medical image, e.g. a radiographic image.
One example of such a system is a computed radiography system wherein a radiation image is recorded on a temporary storage medium, more particularly a photostimulable phosphor screen. In such a system a digital signal representation is obtained by scanning the screen with radiation of (a) wavelength(s) within the stimulating wavelength range of the phosphor and by detecting the light emitted by the phosphor upon stimulation.
Other examples of computed radiography systems are direct radiography systems, for example systems wherein a radiographic image is recorded in a solid state sensor comprising a radiation sensitive layer and a layer of electronic read out circuitry.
Still another example of a computed radiography system is a system wherein a radiographic image is recorded on a conventional x-ray film and wherein that film is developed and subsequently subjected to image scanning.
Still other systems such as a tomography system may be envisaged.
The digital image representation of the medical image acquired by one of the above systems can then be used for generating a visible image on which the diagnosis can be performed. For this purpose the digital signal representation is applied to a hard copy recorder or to a display device.
Commonly the digital signal representation of the image is subjected to image processing prior to hard copy recording or display.
In order to convert the digital image information optimally into a visible image on a medium on which the diagnosis is performed, a multi-resolution image processing method has been developed by means of which the contrast of an image is enhanced.
According to this multi-resolution image processing method an image represented by an array of pixel values is processed by applying the following steps. First the original image is decomposed into a sequence of detail images at multiple scales and a residual image.
Next, the pixel values of the detail images are modified by applying to these pixel values at least one non-linear monotonically increasing odd conversion function with a slope that gradually decreases with increasing argument values.
Finally, a processed image is computed by applying a reconstruction algorithm to the residual image and the modified detail images, the reconstruction algorithm being such that if it were applied to the residual image and the detail images without modification, then the original image or a close approximation thereof would be obtained.
Different embodiments of the above image processing technique has been described extensively in European patent EP 527 525, the processing being referred to as MUSICA image processing (MUSICA is a registered trade name of AGFA-GEVAERT N.V.).
The described method is advantageous over conventional image processing techniques such as unsharp masking etc. because it increases the visibility of subtle details in the image and because it increases the faithfulness of the image reproduction without introducing artefacts.
In order to reduce the noise level in a digital image a method has been applied as described in European patent application EP-A-574 969.
The digital image representation is decomposed into a set of detail images representing image detail at successive resolution levels and a residual image.
At least some of these detail images are then processed as follows. First the noise level in each detail image is estimated. Next a local observation neighbourhood is established around each pixel and the local variance is estimated within that neighbourhood.
Then, the detail images are pixelwise attenuated as a function of the image content and in accordance with the estimated noise level.
More particularly, the local variance is compared with the noise variance and a pixel is attenuated if the local variance approximates the noise variance. No attenuation is applied if the local variance is significantly larger than the noise variance.
In this method the attenuation is determined at a specific scale of the multi-resolution representation independent of the other scales. The noise level at the scale that is processed is taken as a reference.
This approach has the following drawback. In one and the same pixel the attenuation coefficients of successive scales can largely differ because the correlation between pixels at successive scales is limited and because the calculation of the attenuation is a non-linear operation.
This fact introduces additional noise having small magnitude but a rather artificial pattern.
It is an object of the present invention to provide a method that overcomes the above-described problems of the prior art.